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Lecture
Entropy and Sampling Theory
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Related lectures (29)
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Generalized Linear Models
Covers probability, random variables, expectation, GLMs, hypothesis testing, and Bayesian statistics with practical examples.
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Introduces random variables, probability distributions, and expected values through practical examples.
Elements of Statistics: Probability and Random Variables
Introduces key concepts in probability and random variables, covering statistics, distributions, and covariance.
Probability Distributions: Central Limit Theorem and Applications
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Law of Large Numbers: Strong Convergence
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Explores the concept of entropy expressed in bits and its relation to probability distributions, focusing on information gain and loss in various scenarios.
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Explains the Law of Large Numbers and its application to random variables.
